Fake news: Fundamental theories, detection strategies and challenges.
This paper provides a comprehensive overview of fake news research, addressing its challenges and future directions. It discusses the differences between fake news and related concepts like rumors, outlines fundamental theories from…
Application of artificial intelligence techniques to detect fake news
The review article examines the role of machine learning in detecting and combating fake news amid the growing prevalence of social media. It highlights how machine learning techniques, including data mining, deep…
Beyond misinformation: Understanding and coping with the “post-truth” era
The article explores the rise of “post-truth” and “fake news” and their impact on society. It examines how misinformation affects public perception and behavior, the effectiveness of various correction strategies, and the…
How Facebook got addicted to spreading misinformation. He got Facebook hooked on AI
The article discusses the aftermath of the Cambridge Analytica scandal, which revealed a major privacy breach at Facebook and intensified concerns about the platform’s role in amplifying fake news and hate speech.…
Making sense of lies, deceptive propaganda, and fake news
Brennen investigates the widespread problem of deception, propaganda, and fabricated news in contemporary media, analyzing their moral ramifications and influence on public trust. The paper underscores the importance of media literacy and…
Fake News and Cyber-Propaganda in Sub-Saharan Africa: Recentering the Research Agenda.
The book examines the rise of fake news, misinformation, and disinformation, particularly focusing on their impact in Africa. It highlights how the proliferation of social media and smartphones has exacerbated the spread…
The Herman–Chomsky propaganda model: A critical approach to analysing mass media behaviour
The article reviews the Propaganda Model (PM) developed by Edward Herman and Noam Chomsky, as presented in Manufacturing Consent (1988). It examines how the PM explains the behavior and influence of mass…
Why do people share ideologically extreme, false, and misleading content on social media? A self-report and trace data–based analysis of countermedia content dissemination on Facebook and Twitter
The study investigates how individual factors like ideological extremity, social trust, and trust in news media relate to the sharing of countermedia content—web-based information that is ideologically extreme and often misleading. By…
Shifting attention to accuracy can reduce misinformation online
The study finds that while people often share misinformation, their decision to do so is not strongly influenced by the accuracy of the information. Instead, factors other than accuracy, such as attention…
Lazy, not biased: Susceptibility to partisan fake news is better explained by lack of reasoning than by motivated reasoning
The research examines the reasons why individuals are prone to believing false information and determines whether logical reasoning assists in differentiating between genuine and fabricated news stories, regardless of an individual’s political…
